Systems Theory and Automatic Control

State and parameter estimation using moving horizon estimation for directional drilling


In short


Drilling for oil and gas is becoming more and more complex. A precise steering control of the well is required to maximize reservoir contact for increased production and to assure consistent quality of the wellbore. Technologies like rotary steerable systems (RSS) enable drilling of complex three-dimensional wells. Typically, wells are not just vertical but have long horizontal sections for increased reservoir contact which may extend over several kilometers.

Model-based control has shown to be an effective control approach, but modeling the drilling process is challenging due to the complex interaction between drilling-bit and rock, and to the limited transfer of information between the surface and the drilling-bit, furthermore measurement of system states are effected by noise and time delays and model parameters are unknown and are space-variant.

The Moving Horizon Estimation (MHE) is a versatile algorithm that can be used for state and parameter estimation. The MHE uses measurement data in order to estimate the best value of state and parameters. A first version of an MHE algorithm has already been implemented in Matlab/Simulink.

The goals of this master's thesis are:

  • Extending the MHE algorithm in order to consider variable uncertainty on measurement and measurement delays.
  • Testing the MHE algorithm using real data.
  • Testing the MHE using different drilling-bit models.
The thesis will be carried out in collaboration with an important company located in Germany.

Topic Area:

Parameter and state estimation, model identification

Required Prerequisites:

Lectures: System theory
Experience with: MATLAB, Simulink
Language: German or English

Project Start:

As soon as possible

Contact:

Plase send your CV and grades to Bruno Morabito